Small- and medium-enterprises bankruptcy dataset.

Area of Science:

• Business and Economics
• Financial Risk Management
• Data Science

Background:

• Bankruptcy prediction models primarily focus on publicly traded companies, neglecting the significant economic contribution of unlisted small and medium-sized enterprises (SMEs).
• A data gap exists for financial and bankruptcy prediction analysis concerning non-listed SMEs, hindering accurate risk assessment for this vital economic sector.
• Understanding the financial health of SMEs is crucial for economic stability and policy-making, yet data limitations pose a significant challenge.

Purpose of the Study:

• To present a novel dataset of financial ratios for Slovak small and medium-sized enterprises (SMEs) to facilitate bankruptcy prediction research.
• To address the scarcity of data for non-listed companies, enabling more comprehensive bankruptcy prediction models.
• To support academic researchers and industry practitioners in developing and validating bankruptcy prediction tools for SMEs.

Main Methods:

• The dataset comprises 21 distinct financial ratios for Slovak companies across agriculture, construction, manufacturing, and retail sectors.
• Data spans four consecutive years (2013-2016), providing a time-series dimension for analysis.
• All included companies are classified as small and medium-sized enterprises (SMEs) according to European Union (EU) standards.

Main Results:

• The dataset enables the development and testing of bankruptcy prediction models specifically for SMEs.
• It facilitates research on prediction performance using severely imbalanced datasets, a common characteristic of bankruptcy data.
• Published results demonstrate the utility of this dataset in achieving effective bankruptcy prediction for SMEs.

Conclusions:

• The presented dataset fills a critical data gap for bankruptcy prediction in the SME sector.
• It provides a valuable resource for advancing research on financial distress prediction in non-listed companies.
• This data supports improved risk management and financial stability assessments for a significant segment of the economy.